Extending Coverage of Stationary Sensing Systems with Mobile Sensing Systems for Human Mobility Modeling
Extending Coverage of Stationary Sensing Systems with Mobile Sensing Systems for Human Mobility Modeling
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DOI：
10.1145/3411827
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发表时间：
2020-09
影响因子：
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通讯作者：
Yu Yang;Zhihan Fang;Xiaoyan Xie;Fan Zhang;Yunhuai Liu;Desheng Zhang
中科院分区：
文献类型：
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作者：
Yu Yang;Zhihan Fang;Xiaoyan Xie;Fan Zhang;Yunhuai Liu;Desheng Zhang
人类移动性建模在基于位置的服务、移动网络、城市管理和流行病学中有许多应用。以往的人类移动传感方法主要分为两类：固定式传感系统（如监控摄像头和收费站）和移动传感系统（如智能手机应用程序和车辆跟踪设备）。然而，固定传感系统只能提供有限覆盖范围内的人类移动信息（例如，配备摄像头的道路），移动传感系统只能捕获有限数量的人（例如，使用特定智能手机应用程序的人）。在这项工作中，我们设计了一个新的系统Mohen，用异构传感系统来模拟人类的移动。Mohen的关键新颖之处在于用小尺度传感系统从根本上扩展了大尺度静止传感系统的传感覆盖范围。通过对实际城市传感系统数据的评估，我们的系统比它们的性能高出35%，与Oracle方法相比具有竞争力。
Human mobility modeling has many applications in location-based services, mobile networking, city management, and epidemiology. Previous sensing approaches for human mobility are mainly categorized into two types: stationary sensing systems (e.g., surveillance cameras and toll booths) and mobile sensing systems (e.g., smartphone apps and vehicle tracking devices). However, stationary sensing systems only provide mobility information of human in limited coverage (e.g., camera-equipped roads) and mobile sensing systems only capture a limited number of people (e.g., people using a particular smartphone app). In this work, we design a novel system Mohen to model human mobility with a heterogeneous sensing system. The key novelty of Mohen is to fundamentally extend the sensing coverage of a large-scale stationary sensing system with a small-scale sensing system. Based on the evaluation on data from real-world urban sensing systems, our system outperforms them by 35% and achieves a competitive result to an Oracle method.